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@PHDTHESIS{Mester:190118,
author = {Mester, Achim},
title = {{Q}uantitative {T}wo-{L}ayer {I}nversion and {C}ustomizable
{S}ensor-{A}rray {I}nstrument for {E}lectromagnetic
{I}nduction based {S}oil {C}onductivity {E}stimation},
volume = {249},
school = {RWTH Aachen},
type = {Dr.},
address = {Jülich},
publisher = {Forschungszentrum Jülich GmbH Zentralbibliothek, Verlag},
reportid = {FZJ-2015-03058},
isbn = {978-3-95806-035-7},
series = {Schriften des Forschungszentrums Jülich Reihe Energie $\&$
Umwelt / Energy $\&$ Environment},
pages = {viii, 119 S.},
year = {2015},
note = {RWTH Aachen, Diss., 2014},
abstract = {Electromagnetic (EM) measurement methods oer the great
potential to non-invasively and contactlessly obtain
geological and hydrological soil properties of the uppermost
six meters of the subsurface with an areal resolution in the
sub-meter range. The presented work is focused on
small-sized frequency domain `electromagnetic induction'
(EMI) systems which combine the transmitter (Tx) and
receiver (Rx) unit in one portable construction and obtain
the apparent electrical conductivity ($\sigma_{a}$) of the
sensed soil volume by inducing electrical currents and
measuring the responding electromagnetic field. The sensing
depth of EMI instruments depends on the sensor conguration
and in particular the coil orientation and Tx-Rx separation.
In principle, multi-conguration EMI data can be inverted for
the electrical conductivity distribution over depth.
However, there is a demand for efficient inversion
algorithms and high-quality EMI data from different sensing
depths to perform such an inversion. Here, a novel
one-dimensional global-local inversion approach is
implemented which evaluates the mist between EMI data and
forward modeled data for a two-layer soil using a L1-norm
objective function. The global approach is based on a grid
search for reasonable model parameters in combination with
the local-sensitivity forward model. The two soil models
with the smallest misfit are refined using the (local)
simplex search algorithm with the more precise full solution
electromagnetic forward model. The algorithm is analyzed
using synthetic EMI data. Applying the inversion on
quantitative EMI transect data from two commercial devices
with eight different sensor configurations results in a
two-layer electrical conductivity model with lateral and
vertical conductivity changes that are in good agreement
with a collocated electrical resistivity tomography data
set. To improve the depth-resolution beyond available fixed
congurations, a novel EMI prototype system (ElMa1) with
customizable sensor-array is developed, containing multiple
modular sensor units which can be flexibly arranged by the
operator for each survey, ensuring optimal depth-sensitivity
(i.e. coil orientations and Tx-Rx separations) for the
specific investigation. The sensor units consist of
coil-based transmitter and receiver circuits which allow for
the measurement of the magnetic flux and the sensor
impedance in a frequency range between 3 and 33 kHz,
respectively. To allow for flexible sensor congurations,
data processing and signal optimization, the transmitter
current and the receiver voltages are separately digitized
using 24-bit analog-to-digital converters (ADC's) which
provide a high dynamic range and phase stability. For a
measurement time of 0.5 s, the ElMa1 system achieves an
instrumental $\sigma_{a}$-accuracy of 1 mS/m at 20 kHz for
the intended Tx-Rx separation of 1.0 m and an accuracy of 10
mS/m for a less favorable conguration with smaller Tx-Rx
separation of 0.3 m and smaller measurement frequency of 5
kHz, both observed under stable temperature conditions. In
addition, experimental data were corrected for
temperature-induced system drifts by simulating the
electrical circuit of the sensor system using spectral
measurements [...]},
keywords = {Dissertation (GND)},
cin = {ZEA-2},
cid = {I:(DE-Juel1)ZEA-2-20090406},
pnm = {899 - ohne Topic (POF3-899)},
pid = {G:(DE-HGF)POF3-899},
typ = {PUB:(DE-HGF)11 / PUB:(DE-HGF)3},
url = {https://juser.fz-juelich.de/record/190118},
}